hotspots of soil n2o emission enhanced through water ...andg.p.robertson 1,6 n2o is a highly potent...

ARTICLESPUBLISHED ONLINE: 5 JUNE 2017 | DOI: 10.1038/NGEO2963

Hotspots of soil N2O emission enhanced throughwater absorption by plant residueA. N. Kravchenko1*, E. R. Toosi1, A. K. Guber1, N. E. Ostrom2, J. Yu3, K. Azeem4, M. L. Rivers5and G. P. Robertson1,6

N2O is a highly potent greenhouse gas and arable soils represent its major anthropogenic source. Field-scale assessmentsand predictions of soil N2O emission remain uncertain and imprecise due to the episodic and microscale nature of microbialN2O production, most of which occurs within very small discrete soil volumes. Such hotspots of N2O production are oftenassociated with decomposing plant residue. Here we quantify physical and hydrological soil characteristics that lead tostrikingly accelerated N2O emissions in plant residue-induced hotspots. Results reveal a mechanism for microscale N2Oemissions: water absorption by plant residue that creates unique micro-environmental conditions, markedly di�erent fromthose of the bulk soil. Moisture levels within plant residue exceeded those of bulk soil by 4–10-fold and led to accelerated N2Oproduction via microbial denitrification. The presence of large (∅∅∅>35µm) pores was a prerequisite for maximized hotspotN2O production and for subsequent di�usion to the atmosphere. Understanding and modelling hotspot microscale physicaland hydrologic characteristics is a promising route to predict N2Oemissions and thus to develop e�ectivemitigation strategiesand estimate global fluxes in a changing environment.

Extremely high temporal and spatial variability of N2O fluxes isone of the main reasons for persistent difficulties in curbinguncertainties in N2O fluxes1,2, especially from arable soils thatare responsible for the majority of anthropogenic N2O emissions3–6.Despite substantial research efforts7–9, accuracy in predicting N2Oproduction and emission, either via empirical or process-basedmodels, remains surprisingly low9. While the IntergovernmentalPanel on Climate Change has recently proposed a closed globalbudget for N2O, there remains enormous uncertainty regardingprecise source and sink terms10,11. Soil N2O fluxes measuredsimultaneously within several metres of one another often differby a factor of 2 or more12 and day-to-day fluxes can change by anorder of magnitude or more13, requiring intensive sampling regimesto accurately estimate annual fluxes14. Uncertainties associated withpredicting N2O emissions from agricultural soils amended withplant residues, as happens, for example, with cover crops, greenmanure, and land conversion3,15, can be particularly high3–6.

At least some of this variability arises because themajority ofN2Oproduction in soil occurs within very small soil volumes (

ARTICLES NATURE GEOSCIENCE DOI: 10.1038/NGEO2963

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Figure 2 | Decomposition of added plant residue. a,b, X-ray µ-CT images of corn (a) and soybean leaves (b) (green) at the start of the incubationexperiments (top) and after 7 days of incubation (bottom). Scale bars, 1 mm. c, Loss in leaf volume during the incubation determined from the X-ray µ-CTimages. Data are means for plant residue type and pore sizes averaged across both levels of WFPS and agricultural managements, error bars indicate s.e.m.(n=4), asterisks indicate significant di�erences between pore sizes at p

NATURE GEOSCIENCE DOI: 10.1038/NGEO2963 ARTICLES

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Figure 3 | Cumulative N2O emitted during 110 days (bars) and proportionof N2O generated by denitrification during 7 days of incubation (boxes).Data are means for plant residue and pore treatments averaged across bothlevels of WFPS and agricultural practices, error bars indicate s.e.m. (n= 12),asterisks represent statistically significant di�erences between small andlarge pores within plant types (∗∗p

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Figure 4 | Relative changes in O2 during the first 4 days of soil microcosm incubations. On the y axis is the distance along the oxygen sensor from the leaf(0) to the top of the soil sample (20,000 µm); on the x axis are the relative cumulative changes in O2 levels as compared with pre-incubation for large- andsmall-pore microcosms, respectively. The dots represent means, the shaded areas indicate s.e.m., the vertical grey bar marks the position along the sensorwhere there was a significant di�erence between microcosms with soybean leaves and microcosms with no leaves (p

NATURE GEOSCIENCE DOI: 10.1038/NGEO2963 ARTICLES5. Petersen, S. O., Mutegi, J. K., Hansen, E. M. & Munkholm, L. J. Tillage effects

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AcknowledgementsWe are indebted to K. Kahmark for conducting N2O analyses; to H. Gandhi and J. Haslunfor conducting site-preference measurements; and to the KBS LTER team for agronomicmanagement of the field experiment. Funding has been provided by the National ScienceFoundation’s Long-Term Ecological Research Program (DEB 1027253), by the NationalScience Foundation’s Geobiology and Low Temperature Geochemistry Program (Awardno. 1630399), by the Department of Energy Great Lakes Bioenergy Research Center(DOE Office of Science BER DE-FC02-07ER64494), by Michigan State University’sAgBioResearch (Project GREEEN), and by Michigan State University’s DiscretionaryFunding Initiative. Portions of this work were performed at GeoSoilEnviroCARS (TheUniversity of Chicago, Sector 13), Advanced Photon Source (APS), Argonne NationalLaboratory. GeoSoilEnviroCARS is supported by the National Science Foundation -Earth Sciences (EAR-1128799) and Department of Energy—GeoSciences(DE-FG02-94ER14466).

Author contributionsA.N.K. developed concepts, conducted data analyses and wrote the paper. E.R.T.designed, led and conducted the research, and contributed to writing. A.K.G. and N.E.O.contributed to development of research concepts, research conduct and writing. J.Y., K.A.and M.L.R. contributed to research conduct. G.P.R. contributed to the development ofresearch concepts and writing.

Additional informationSupplementary information is available in the online version of the paper. Reprints andpermissions information is available online at www.nature.com/reprints. Publisher’s note:Springer Nature remains neutral with regard to jurisdictional claims in published mapsand institutional affiliations. Correspondence and requests for materials should beaddressed to A.N.K.

Competing financial interestsThe authors declare no competing financial interests.

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ARTICLES NATURE GEOSCIENCE DOI: 10.1038/NGEO2963MethodsSoil sampling and preparation. Soil samples were collected from conventionallyand organically managed corn–soybean–wheat rotation treatments in the MainCropping System Experiment of the Kellogg Biological Station Long-TermEcological Research site (KBS LTER). Soils are Typic Alfisols of Kalamazoo andOshtemo series, with properties common to the deciduous forest zone of the USMidwest and Europe. The conventional treatment obtains agrochemical inputsconsistent with recommendations of Michigan State University Extension. Theorganic treatment does not receive any chemical inputs but includes cover crops(cereal rye and red clover) as part of the rotation. Additional climate, soils andagronomic details are available elsewhere49. KBS LTER was established in 1989 andsince then the organic management has resulted in greater soil C levels than theconventional management50,51.

Soil samples were collected in autumn of 2014, after corn harvest, from0–15 cm depth, representing the Ap horizon. Air-dried samples were used toprepare soil materials of two contrasting pore characteristics, with predominantlylarge and small pores, respectively (Supplementary Fig. 1). The large-pore materialwas obtained by sieving air-dry soil and collecting the 1–2mm sieved fraction. Tominimize inherent differences, the small-pore material was created from thelarge-pore material. For that, the large-pore material was crushed and sieved, andthe 0.05–0.1mm fraction so-produced was collected for the experiments. Bydesign, the large- and small-pore materials had very substantial differences in theirPSD. Despite their identical origin, crushing and sieving had unavoidable effects onparticle-size distributions of the materials and on the availability of soil C todecomposers39,40 (Supplementary Table 3).

Soil microcosms. Soil microcosms (8mm diameter× 10mm height) wereconstructed using the two soil materials. We constructed the microcosms with drycorn and soybean leaves (Supplementary Fig. 3) and also control microcosmswithout leaves. All samples were constructed so as to maintain the same bulkdensity of 1.1 g cm−3; thus, all treatments had the same 58% total porosity.

Leaf disc preparation. Corn and soybean were harvested 75 d after germination.Leaf discs (∅ 7mm) were prepared by cutting the leaves into circles using a holepunch. The leaf discs were then flat dried in a herbarium drying press. The weightof each individual leaf disc was recorded before it was placed into the microcosm(Supplementary Table 4).

Incubation experiment.Microcosms were incubated at two soil moisture levelscorresponding to water-filled pore spaces (WFPS) of 30% and 45% (SupplementaryTable 1). These WFPS levels reflected the following hydrological characteristics ofthe studied soil: WFPS of 30% corresponded to the porosity of 1–2mm soil fractionused in this study—that is, the condition at which large pores were not filled withwater, and, thus, served as conduits for free gas diffusion. WFPS of 45%corresponded to the field capacity of the microcosms made of 1–2mm soilfraction, the state when capillary menisci between soil aggregates were expected torestrict free gas flow. The porosity of 1–2mm fraction fragments was assessed fromX-ray µ-CT images, whereas the field capacity was measured by free drainage ofwater-saturated microcosms.

Relevant amounts of water were added separately to the bottom and top partsof the microcosm during its construction to ensure even soil moisture distributionthrough the entire sample. Each microcosm unit was placed into a 40ml testtube containing 1ml water and capped with a stopper. Four replicated microcosmsamples were incubated for each of the 24 experimental treatments (3 substrate levels(corn, soybean, control)× 2 agricultural systems× 2 pore sizes× 2 soil moisturelevels) for a total of 96 microcosms. The samples were incubated for 110 days,during which the headspace was sampled on days 1, 3, 7, 14 and thereafter every12 days, for a total of 11 sampling events. At each sampling event, the headspacegas was sampled into pre-evacuated 5ml Exetainers and analysed for N2O usingan Agilent 7890 GC equipped with flame ionization and electron capture detectors.

Moisture levels in leaf discs. To determine gravimetric moisture contents of leafdiscs during the incubation we conducted a supplementary experiment with aseparate set of microcosms created using air-dried leaves as described above. Soilfrom conventional management practice was used in this analysis. The microcosmswere allowed to equilibrate with added water for 4 h, a time adequate for completewater redistribution through the microcosm, yet sufficiently short to precludemeasurable leaf decomposition. Then we disassembled the microcosms, weighedthe leaf discs, and calculated gravimetric water content of each leaf. In cases whenthere was soil attached to wet leaves, the leaves were weighed and dried and theamount of attached soil was determined by weighing the dry soil separated fromthe leaves, and then subtracted.

X-ray µ-CT scanning and image analyses. For image analysis, an additional set ofmicrocosms with corn and soy leaves were subjected to incubations and scanned atday 7, 14 and 24. Scanning was destructive: that is, to ensure higher accuracy in

estimating leaf sizes, prior to scanning the samples were air-dried and thus notused in further incubations. We scanned 1–3 replicates for each of the 48 treatment× day combinations (2 substrate levels (corn, soybean)× 2 agricultural systems×2 pore sizes× 2 soil moisture levels× 3 sampling dates), for a total of 71 scannedmicrocosm samples. X-ray µ-CT scanning was conducted on the bending magnetbeam line, station 13-BM-D of the GeoSoilEnvironCARS at the Advanced PhotonSource, Argonne National Laboratory, with resolutions 3–6 µm (ref. 52).Quantification of the plant leaf volume within each microcosm was conductedusing image segmentation and particle analysis tools available in ImageJ(http://rsbweb.nih.gov/ij)25,53. To obtain detailed pore characteristics of the createdsoil materials a subset of samples was scanned at 2 µm resolution. In the samplesfrom the subset, pores were identified using the indicator kriging method54,55 andtheir size distributions were obtained using a medial axis approach implemented in3DMA-Rock software56,57. To visualize the location of the water added to themicrocosms, we prepared a subset of control samples using 10% KI solution. Thesamples were scanned at 2 µm resolution at two energy levels, namely, 33.269 keV,which is above the iodine K absorption edge and 33.108, which is below the edge.The two data sets were subtracted, which clearly identifies the location of theiodine and hence the liquid added to the system.

Spatial pattern in O2 distribution. A supplementary experiment was conducted toassess the spatial patterns in O2 distribution within the samples using opticaloxygen sensors (optodes). The non-invasive sensors measure partial pressure of O2by recording fluorescence quenching, where oxygen quenches a photoluminescentsubstance (for example, ruthenium(II)-diimine-complex orplatinum(II)-porphyrin)58. The sensor foil (SF-PSt3- NAU-YOP, PreSens, PrecisionSensing GmbH), 2× 0.5 cm, was glued to the inner side of the container with themicrocosm sample and the leaves placed at the bottom of the microcosms (Fig. 4).The sensor signal was read every 20min for 4 days from the start of the incubation.To reduce noise, the original 25-µm-resolution measurements were aggregated to100 µm resolution. Relative deviation of O2 levels from the pre-incubation averagewas used to asses O2 changes.

Gas diffusivity calculations. The information on pore volumes inside and betweensoil fragments and their air-filled status obtained using X-ray µ-CT was used toestimate relative gas diffusion coefficients in the microcosms. We used an approachbased on the conceptual model of a bimodal porous medium developed byResurreccion and colleagues59. The ratio between the gas diffusion coefficients inthe soil, Dp, and in the free air, Do, changes with soil air content as:

DpDo=

{(ε1Φ1

)N1εX11 ε≤Φ1

ΦX11 +F2εX22 ε>Φ1

(1)

whereΦ1 is the inter-clod porosity (cm3 cm−3); ε1, ε2 and ε are the inter-clod andintra-clod, and total air-filled porosities, respectively (cm3 cm−3); X1 and X2 are thedry-region pore connectivity factors of inter- and intra-clod pores (dimensionless);and N1 and F2 are the empirical parameters (dimensionless).

Parameters of equation (1) were set on the basis of studies by Currie60,61 asX1=1.56, N1=1.82 for the 0.05–0.1mm aggregate fraction, and X1=1.73,X2=1.21 and F2=0.71 for the 1–2mm aggregate fraction, respectively.

SP analysis. The relative importance of bacterial denitrification (includingnitrifier-denitrification) to total N2O production was determined as described byOstrom and colleagues36. Pure culture studies demonstrate that SP values of 33 to37 and−10 to 0h, respectively, indicate N2O production from hydroxylamineoxidation+ fungal denitrification and bacterial denitrification62,63. On the basis ofthese values the proportion of N2O derived from denitrification can be determinedfrom the SP value of soil-derived N2O (ref. 27). As ambient air was used as theheadspace in our soil microcosms, the SP of soil-derived N2O was calculated on thebasis of the isotope values for ambient air (in blanks) and headspace gas analysed atthe end of the 7 day incubation period27. SP was determined only on incubationslasting 7 days, the period of time that encompassed the highest rates of N2Oproduction. To obtain sufficient N2O for isotope analyses larger microcosms(∅ 25mm× 10mm) were prepared following the same procedures as describedabove. The N2O obtained from microcosms was analysed using a Trace Gas System(Elementar) interfaced to an Elementar Isoprime 100 mass spectrometer fordetermination of bulk δ15N, δ18O and SP62,63. Within the Trace Gas System, waterand CO2 are removed using chemical scrubbers (magnesium perchlorate andCarbosorb, respectively) and N2O is chromatographically separated from theresidual CO2 on a Porapak Q column that is interfaced to the massspectrometer62,63. The Isoprime multi-collector mass spectrometer simultaneouslymonitors 5 masses of interest for N2O isotopomers: 30, 31, 44, 45 and 46. We followthe convention of Toyoda and Yoshida64 in defining the central and outer nitrogenatoms as α and β, respectively. We applied corrections for the contribution of 17O tomasses 31 and 45 and for a small degree of rearrangement of 15N between the α andβ positions within the ion source64.


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NATURE GEOSCIENCE DOI: 10.1038/NGEO2963 ARTICLESStatistical analysis. Data analyses were conducted using the PROCMIXEDprocedure of SAS (SAS, 2012). For one-time measurements, for example,cumulative amounts of emitted N2O, the statistical model included fixed effects ofthe studied factors and their interactions and the random effect of the experimentalblocks. The studied factors were agricultural management practices, plant residuetypes, soil WFPS levels and soil pore size distribution treatments. Formeasurements that were taken at multiple times from each microcosm, forexample, N2O emission rates, the repeated measures approach was used, withindividual microcosms nested within respective treatments and treated as therandom effect and an error term. Normality and homogeneity of varianceassumptions were assessed using plots of the residuals. Lack of normality in theN2O data was addressed by log-transformation and unequal variance analysis wasused as needed on the basis of Bayesian information criterion values65. Significantinteraction effects were examined using analysis of simple effects, also known asslicing66. The differences between control microcosms and the microcosms withplant residue, also known as plant residue-induced effects, were quantified usingcontrast statements. Likewise, the differences between plant residue-induced effectsin different treatments were assessed by contrasts. Results were reported asstatistically significant at p

In the format provided by the authors and unedited.

Supporting Information

Hotspots of soil N2O emission enhanced through water absorption by plant residue

A. N. Kravchenko*, E. R. Toosi, A.K. Guber, N. E. Ostrom, J. Yu, K. Azeem, M. L. Rivers, and

G. P. Robertson

*Corresponding author:

Email: [email protected]

Phone: 517.353.0469

This file includes:

Figures S1-S3

Tables S1-S4

Hotspots of soil N2O emission enhanced throughwater absorption by plant residue


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Figure S2 | N2O emission rates during soil microcosm incubation. The main graph presents the effect of adding plant residue to soil microcosms (means, error bars indicate SEs, letters mark significant differences between substrate treatments at p

Figure S3 | Hotspot microcosm construction. (a) 3D X-ray µCT images of the microcosms with large (left) and small (right) pore materials. (b) A 0.5 g of soil material (brown) was placed in a 3 mL plastic container, moistened to one of the two studied WFPS levels and packed to bulk density of 1.1 g/cm3. The leaf disk (green) was placed on top and the second half of the soil material was packed onto the disk and moistened. A perforated Teflon disk at the bottom of the column (yellow) retained the soil while maintaining air flow.





Table S1. Soil moisture content and gas diffusion settings in the large and small pore materials used in the study at 30% and 45% WFPS levels.

Pore size treatment WFPS, %

Gravimetric soil moisture content, %

Gas diffusion coefficient, Dp/Do

Large 30 15 0.17 45 24 0.16 Small 30 15 0.11 45 24 0.04





Table S2. Percent of N2O produced via denitrification in the microcosms of the two studied WFPS levels at the three substrate treatments (means averaged across both pore size treatments, standard errors are shown in parentheses, means within the same row followed by the same letter are not significantly different from each other (p

Table S3. Soluble organic C in the materials of the large and small pore treatments in conventional and organic agricultural managements (means, standard errors are shown in parentheses, different letters mark statistically significant differences among the treatments and managements at P

Table S4. Characteristics of corn and soybean leaves used in the incubations (means, standard errors are shown in parentheses, n=6).

Plant residue

Leaf weight, mg

C concentration, %

N concentration,

%

C:N ratio N input with leaf, mg

Corn 1.16 (0.03) 44.4 (0.1) 3.8 (0.1) 11.8 (0.2) 0.044 Soybean 1.23 (0.04) 38.6 (0.4) 5.3 (0.2) 7.4 (0.3) 0.065





Hotspots of soil N2O emission enhanced through water absorption by plant residueMicro-environments within plant residue hotspotsLocal anoxia within plant residues and denitrificationLarge pores drive fate of N2O produced within hotspotsConcluding remarksMethodsFigure 1 Gravimetric moisture content of corn and soybean leaves used in the incubations.Figure 2 Decomposition of added plant residue.Figure 3 Cumulative N2O emitted during 110 days (bars) and proportion of N2O generated by denitrification during 7 days of incubation (boxes).Figure 4 Relative changes in O2 during the first 4 days of soil microcosm incubations.Figure 5 Differences in N2O emission rates between soil microcosms with plant residues and control soil during 1–14 days of incubation.ReferencesAcknowledgementsAuthor contributionsAdditional informationCompeting financial interestsMethodsSoil sampling and preparation.Soil microcosms.Leaf disc preparation.Incubation experiment.Moisture levels in leaf discs.X-ray -CT scanning and image analyses.Spatial pattern in O2 distribution.Gas diffusivity calculations.SP analysis.Statistical analysis.Data availability.

References

hotspots of soil n2o emission enhanced through water ...andg.p.robertson 1,6 n2o is a highly potent...

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